Invention Grant
- Patent Title: Automatic document classification using machine learning
-
Application No.: US16559322Application Date: 2019-09-03
-
Publication No.: US11238313B2Publication Date: 2022-02-01
- Inventor: Hooman Majidzadeh Rezvani , Andrii Matiukhov , Takashi Oguma , Sang Lee , Charles Henze , Hiroshi Manabe , Christian Olmstead Holmes
- Applicant: KYOCERA DOCUMENT SOLUTIONS INC.
- Applicant Address: JP Osaka
- Assignee: KYOCERA DOCUMENT SOLUTIONS INC.
- Current Assignee: KYOCERA DOCUMENT SOLUTIONS INC.
- Current Assignee Address: JP Osaka
- Agency: GrowIP Law Group LLC
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/00 ; G06N20/00

Abstract:
Automatic document classification using machine learning may involve receiving inputs that assign documents to classifiers, which define document classification rules for a classification model. The computing device may train the classification model using a machine learning technique that assigns each document of a second set of documents to destinations based on the document classification rules. The computing device may also receive a template design for each destination that specifies metadata to extract for a document type corresponding to documents assigned to the destination. The computing device may subsequently classifying a particular document using the classification model, which may involve assigning the particular document to a given destination of the plurality of destinations based on the document classification rules, and exporting metadata from the particular document using the template design associated with the given destination.
Public/Granted literature
- US20210064866A1 AUTOMATIC DOCUMENT CLASSIFICATION USING MACHINE LEARNING Public/Granted day:2021-03-04
Information query